Finding 2-Factors Closer to TSP Tours in Cubic Graphs 18th Aussois Combinatorial Optimization Workshop January 6-10, 2014 1 Sylvia Boyd (U. Ottawa) Satoru.

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Presentation transcript:

Finding 2-Factors Closer to TSP Tours in Cubic Graphs 18th Aussois Combinatorial Optimization Workshop January 6-10, Sylvia Boyd (U. Ottawa) Satoru Iwata (U. Tokyo) Kenjiro Takazawa (Kyoto U. / Lab. G-SCOP)

Petersen’s Theorem 2 Every bridgeless cubic graph has a perfect matching Every bridgeless cubic graph has a 2-factor [1891] G=(V,E): Bridgeless Cubic Graph Thm. = 2-edge-connected deg(v) = 3 for every v in V

Schönberger’s Theorem 3 G has a perfect matching including e* G has a 2-factor excluding e* e* [1935] G=(V,E): Bridgeless Cubic Graph e* in E  O(n log 4 n) algorithm [Biedl, Bose, Demaine, Lubiw 2001] n = |V| Thm.

Kaiser & Škrekovski’s Theorem 4 [2008] G=(V,E): Bridgeless Cubic e* in E G has a 2-factor excluding e* and covering all 3- and 4-edge cuts 3-edge cut4-edge cutNot a 4-edge cut Thm.

2-factors and TSP Tours 5 TSP tour = 2-factor of one cycle of length n  2-factor without cycles of length k or less : C ≤k -free 2-factor (in simple graphs)  ✓ C ≤3 -free ✓ C ≤4 -free k = n/2  TSP tour Relax

Complexity of C ≤k -free 2-factors 6 UnweightedWeighted k ≥ 5NP-hard [Papadimitriou ’80] NP-hard k = 4(a) OPEN(b) NP-hard [Vornberger ’80] k = 3(c) P [Hartvigsen ’84] (d) OPEN k = 2PP Bipartite graphs (a) : P [Hartvigsen ’06, Pap ’07] (b) : NP-hard for general weight [Király 00] P if the weight hass a special property [Makai ’07, T. ’09] Subcubic graphs (a) : P [Bérczi & Végh ’10] (c) : P [Bérczi & Végh ’10, Hartvigsen & Li ’11] (d) : P [Vornberger ’80, Kobayashi ’10, Hartvigsen & Li ’13]

2-factors Covering Cuts 7 TSP tour = 2-factor covering all edge cuts  2-factor covering all 3-edge cuts  C ≤3 -free  2-factor covering all 3,4-edge cuts  C ≤4 -free G: 3-edge-connected cubic G: Cubic  2-factor covering prescribed edge cuts Relax

Our Results 8 (2) An O(n 3 )-algorithm for finding a 2-factor covering all 3-, 4-edge cuts in bridgeless cubic graphs (3) A 6/5-approx. algorithm for the minimum 2-edge-connected subgraph problem in 3-edge-connected cubic graphs  Constructive proof for [Kaiser, Škrekovski 2008]  Start with the 2-factor found by Algorithm (2)  Previous ratio: 5/4 for 3-edge-connected cubic graphs [Huh 2004] (1) - An O(n 3 )-algorithm for finding a min.-weight 2-factor covering all 3-edge cuts in bridgeless cubic graphs - Polyhedral description Application

Contents 9 Introduction Summary (2) An O(n 3 ) algorithm for finding a 2-factor covering all 3-, 4-edge cuts in bridgeless cubic graphs (3) A 6/5-approx. algorithm for the minimum 2-edge-connected subgraph problem in 3-edge-connected cubic graphs

Proper 3- and 4-Edge Cuts 10 S S  3- and 4-edge cuts covered by every 2-factor A 3-edge cut δ(S) is proper 2 ≤|S|≤ n - 2 A 4-edge cut δ(S) is proper 3 ≤|S|≤ n - 3 δ(S) Find a 2-factor F satisfying:  Covering all proper 3- and 4-edge cuts Goal V-S  Excluding an edge e* in E v e

Covering 3-Edge Cuts 11 (1) Find a proper 3-edge cut δ(S) S (2) Contract V – S, S S (3) Recurse  F 1 (4) Recurse  F 2 (Exclude e*)  Smaller bridgeless cubic graphs e* (5) Return F = F 1 + F 2 G1G1 G2G2 F covers all 3- & 4-edge cuts Gluing technique in [Cornuéjols, Naddef, Pulleyblank 85]

Covering 4-Edge Cuts 12 (1)Find a proper 4-edge cut δ(Y) = {e 1,e 2,e 3,e 4 } (Y: minimal) Y Y (2) Contract V - Y (3) For any pair e i,e j, check if G 2 has a 2-factor including {e i,e j } Y (4) Contract Y to v Y, split v y according to (3) (5) Recurse  F 1 e1e1 e2e2 e3e3 e4e4 e1e1 e3e3 e2e2 e4e4 e* Bridgeless Cubic  {e 1,e 2,e 3,e 4 } in F 1 f* (6) Return F = F 1 + F 2 F2F2 F1F1 F2F2 F1F1 G2G2 G1G1

Contents 13 Introduction Summary (2) An O(n 3 ) algorithm for finding a 2-factor covering all 3-, 4-edge cuts in bridgeless cubic graphs (3) A 6/5-approx. algorithm for the minimum 2-edge-connected subgraph problem in 3-edge-connected cubic graphs

The Minimum 2-Edge-Connected Subgraph Problem 14 Input: Graph G = (V, E) Goal: 2-edge-connected subgraph (V, E’) minimizing |E’|  Hamilton cycle  Optimal solution  n: lower bound Khuller, Vishkin (‘94), Cheriyan, Sebő, Szigeti (‘98) Vempala, Vetta (‘00), Jothi, Raghavachari, Varadarajan (‘03) Sebő, Vygen (‘13) : 4/3-approx. General graphs 3-edge-connected cubic graphs Huh (‘04) : 5/4-approx. This talk: 6/5-approx

Rough Idea 15 F: 2-factor covering all 3- and 4-edge cuts  Cycles of length ≥ 5 2 extra edges for each cycle  7/5-approx. 

u* Saving 1 Edge in a Small Cycle 16 C: Small cycle in F We have reached at v* in V(C)  G[V(C)] has a Hamilton path from v* to u*, and we can leave for another cycle from u* Lemma v*  Small cycle: Size 5--9  Large cycle: Size ≥ 10 Cycles in F :

Algorithm Sketch HH  Back to H  Update H  Back to a large cycle C L  Compound C L --C L H CLCL

v Algorithm Sketch 18  Back to a small cycle C S (at v in V(C S ))  Compound v--v H CSCS If G is 3-edge-connected, there exists an edge from to another cycle. Lemma

Approximation Ratio 19 |E(H)| ≤ 6n/5 - 1 Thm. (Pf.)x = # small cycles in the initial 2-factor F y = # large cycles in the initial 2-factor F |E(H)| ≤ n + 2(x + y - 1) – (x - 1) Save 1 edge for each small cycle 2 extra edges for each cycle = n + x + 2y -1 ≤ 6n/ x + 10 y ≤ n

Contents 20 Introduction Summary (2) An O(n 3 )-algorithm for finding a 2-factor covering all 3-, 4-edge cuts in bridgeless cubic graphs (3) A 6/5-approx. algorithm for the minimum 2-edge-connected subgraph problem in 3-edge-connected cubic graphs

For bridgeless cubic graphs:  A 2-factor covering all 3- and 4-edge cuts: Algorithm  A min-weight 2-factor covering all 3-edge cuts: Algorithm Polyhedral description Summary 21 For 3-edge-connected cubic graphs  6/5-approx. algorithm for the min. 2-edge-connected subgraph problem Min-weight 2-factor covering all 3- and 4-edge cuts in bridgeless cubic graphs 6/5–approx. algorithm for the min. 2-edge-connected subgraph problem in bridgeless cubic graphs Open Problems

22

2-Factors Covering 3-Edge Cuts [Weighted] 23 2-factor polytope [Edmonds 1965] x(δ(v)) = 2 v in V x(Y) – x(δ(S) - Y) ≤ |Y| - 1 S ⊂ V, Y ⊆ δ(S), Y: matching, |Y|: odd 0 ≤ x(e) ≤ 1 e in E Additional constraint x(δ(S)) = 2 S ⊂ V, δ(S) is a 3-edge cut Thm. The above constraints determine the polytope of the 2-factors covering all 3-edge cuts

Algorithm Sketch 24 (1) Find a proper 3-edge cut δ(S) = {e 1,e 2,e 3 } (S: minimal) S (2) Contract V – S, S S eiei G1G1 G2G2 (3) In G 2, find a min. weight 2-factor F i excluding e i (i=1,2,3) FiFi (3) In G 1, add extra weight x i for e i, where x 1 + x 2 = L 3, x 2 + x 3 = L 1, x 3 + x 1 = L 2  L i = w(F i ∩ E[S]) (4) Recurse in G 1 Gluing technique in [Cornuéjols, Naddef, Pulleyblank 85]